Optical navigation or more generally displacement sensing and estimation permits measurement of displacements through the use of image cross-correlations. One known displacement measurement technique involves acquiring displaced images of an object or a web on the surface of the object, correlating the images with respect to one another, and deriving a translation vector based on a maximum likelihood formulation. One may acquire displaced images in a variety of ways, including taking time-separated acquisitions when the object, camera, or both are moving; taking images with multiple cameras that are offset from one another; or some combination involving motion and multiple cameras.
Systems that correlate displaced images and generate displacement estimates have been used with success in devices such as optical mice for control of cursor movement according to measured displacements relative to underlying surfaces. However, such displacement measurement techniques have not been thought suitable for applications where the required accuracy of the displacement measurement may be less than the wavelength used in imaging.
Known systems for precision alignment or measurement of small displacements have a number of common drawbacks. In particular, such systems are generally complex and expensive. Additionally, many such systems are inflexible in requirements, e.g., space and/or isolation requirements, making implementations awkward or impossible in many applications. Many measurement systems require specific patterns such as grating patterns to be laid-down on the object being measured to produce moire or diffraction patterns. Such patterns can be highly regular, so that spatial-uniqueness (or false matches) can become an issue. Also many precision measurement systems that are accurate at small dimensions are specifically designed for alignment sensing and cannot track movement or provide quantitative displacement information. Further, the systems that do provide quantitative displacement information are often unable to do so in real-time because of required scanning processes or significant post-processing.
Current measurement systems for precision tracking of a small object can be broadly categorized as being optical or non-optical measurement systems. An interferometer is one example of an optical measurement system that can precisely measure the position or velocity of an object by interfering or comparing a beam reflected from the object with a reference beam. Other optical interference based measurement systems are known that track object movement by measuring the movement of a diffraction patterns that a grating mounted on the object generates. Non-optical techniques are also available or proposed for tracking object movement. Examples of non-optical systems for precise measurements of small displacements include a Scanning Electron Microscope (SEM), an Atomic Force Microscope (AFM), or a capacitance sensing system.
An advantage of optical measurement systems generally when compared to the non-optical systems is the availability of precise and relatively inexpensive components such as beam sources and lenses. However, many optical measurement systems are limited to measurement accuracies that are greater than or about equal to the wavelength of the light used, and the wavelengths of visible light for which precision components are readily available are larger than the accuracies required for nanometer scale measurements. Optical systems for tracking movement with nanometer scale accuracies or accuracies shorter than visible light wavelengths are desired.